below marketmost similar roles pay hereabove market
This role pays more than
59%
of similar roles. Most pay
$178,050–$231,000
— the blue band above.
At the midpoint, this role pays about
$209k
versus about
$205k
for comparable roles.
Based on 240 similar postings.
Employer
About Microsoft
Microsoft Corporation is a global technology leader producing software, hardware, and cloud services including Windows, Office 365, Azure cloud platform, Xbox gaming, and Surface devices. Industry: Software & Cloud Computing
Microsoft currently has
661 open roles
on FindRole.
Listed pay typically runs
$119,800–$234,700
across 633 roles with salary data.
The Principal Applied AI Engineer joins the ACES CØDE engineering team to build domain-specific agents and services that transform Azure customer support from reactive, human-dependent workflows into AI-first systems. As a hands-on technical architect and senior developer, you will design and implement production agentic AI systems, including LLM orchestration, multi-agent coordination, retrieval-augmented generation (RAG) pipelines, and tool integrations. You will write production-quality C# and Python code to build foundational components, establish engineering standards, and lead complex technical initiatives across organizational boundaries. The role focuses on solving the problem of high operational demand by turning customer signals into autonomous resolution systems. You will ensure these services meet rigorous standards for correctness, latency, and safety while embedding responsible AI principles and prompt-injection defenses into the architecture.
Architect and build production agentic AI systems including LLM orchestration, RAG pipelines, and multi-agent workflows.
Write, review, and maintain production-quality C# and Python code for critical platform components.
Translate ambiguous customer support scenarios into clear technical requirements and scalable system architectures.
Establish engineering standards for API contracts, code quality, evaluation practices, and observability for AI services.
Design and implement evaluation frameworks using rubrics, golden datasets, and judge models to define quality thresholds.
Ensure AI services meet strict standards for correctness, availability, latency, cost, and safety.
Embed responsible AI principles, including prompt-injection defenses and data boundary enforcement, into system architectures.
Mentor engineers in system design and applied AI to raise the technical capability of the organization.
What we're looking for
Bachelor's Degree in Computer Science or related technical field and 6+ years of technical engineering experience with coding in languages like C, C++, C#, Java, JavaScript, or Python (or equivalent experience).
Ability to pass the Microsoft Cloud background check.
15 years of professional software engineering and enterprise architecture experience designing and operating complex production software systems at enterprise scale (preferred).
Master's Degree in Computer Science with 8+ years of experience or a Bachelor's Degree with 12+ years of experience in technical engineering (preferred).
Deep hands-on software development background combined with enterprise architecture expertise to translate requirements into scalable, resilient, and maintainable system architectures (preferred).
Proficiency in C# and/or Python with demonstrated ability to design and implement production-quality services and distributed systems (preferred).
Experience with applied AI systems, including LLM-based applications, prompt engineering, RAG architectures, agent frameworks, or machine learning services (preferred).
Experience with cloud platforms (preferably Azure) and cloud-native engineering practices like microservices, APIs, containers, CI/CD, and observability (preferred).
Python
C#
Azure
LLM
RAG
Agentic AI
Azure AI Foundry
Azure OpenAI
CI/CD
Prompt Engineering
Microservices
Cosmos DB
RBAC
Managed Identities
System Design
Data Structures
Algorithms
C++
Java
JavaScript
Python
C#
Java
C++
JavaScript
Generative AI
Large Language Models
Agentic AI
Azure AI Foundry
Copilot Studio
Power Platform
Retrieval-Augmented Generation
Prompt Engineering
Distributed Systems
APIs
Observability
Data Governance